import torch from transformers import AutoModelForCausalLM, AutoTokenizer from PIL import Image torch.set_default_device("cuda") model = AutoModelForCausalLM.from_pretrained( "../Imp-v0-3b", torch_dtype=torch.float16, device_map="auto", trust_remote_code=True) tokenizer = AutoTokenizer.from_pretrained("../Imp-v0-3b", trust_remote_code=True) text = "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: \nWhat are the colors of the bus in the image? ASSISTANT:" image = Image.open("images/bus.jpg") input_ids = tokenizer(text, return_tensors='pt').input_ids image_tensor = model.image_preprocess(image) output_ids = model.generate( input_ids, max_new_tokens=100, images=image_tensor, use_cache=True)[0] print(tokenizer.decode(output_ids[input_ids.shape[1]:], skip_special_tokens=True).strip())